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Models of roundabout lane capacity

Models of roundabout lane capacity
Models of roundabout lane capacity
Accurate roundabout capacity models are essential for optimal roundabout designs, but there exist significant differences in the predicted capacities of various state-of-the-art models and in their included explanatory variables. An empirical study into roundabout lane entry capacity was thus performed in the U.K. using data from 35 roundabout entry lanes, where various model forms and explanatory variable sets were tested. Two regression models and an artificial neural network were developed. A negative exponential relationship with circulating flow predicted lane capacity better at high and low circulating flows, and better reflected the overall trends in the aggregated capacity data, compared to a linear model. The regression models performed relatively well and provided better information on the impacts of the variables than the neural network. The models consistently suggest that entry-exit separation and flows exiting on the same arm have stronger significant effects on capacity than variables such as entry angle and entry radius. These findings could thus contribute to an improved understanding of the variables that affect entry lane capacity and therefore the development of better roundabout capacity models.
0733-947X
1-8
Yap, Yok Hoe
3a598422-0b9f-4932-86bc-ab7b7da833a5
Gibson, Helen
f3044081-b021-4f0e-b373-7ae24551c7a7
Waterson, Ben
60a59616-54f7-4c31-920d-975583953286
Yap, Yok Hoe
3a598422-0b9f-4932-86bc-ab7b7da833a5
Gibson, Helen
f3044081-b021-4f0e-b373-7ae24551c7a7
Waterson, Ben
60a59616-54f7-4c31-920d-975583953286

Yap, Yok Hoe, Gibson, Helen and Waterson, Ben (2015) Models of roundabout lane capacity. ASCE Journal of Transportation Engineering, 141 (7), 1-8. (doi:10.1061/(ASCE)TE.1943-5436.0000773).

Record type: Article

Abstract

Accurate roundabout capacity models are essential for optimal roundabout designs, but there exist significant differences in the predicted capacities of various state-of-the-art models and in their included explanatory variables. An empirical study into roundabout lane entry capacity was thus performed in the U.K. using data from 35 roundabout entry lanes, where various model forms and explanatory variable sets were tested. Two regression models and an artificial neural network were developed. A negative exponential relationship with circulating flow predicted lane capacity better at high and low circulating flows, and better reflected the overall trends in the aggregated capacity data, compared to a linear model. The regression models performed relatively well and provided better information on the impacts of the variables than the neural network. The models consistently suggest that entry-exit separation and flows exiting on the same arm have stronger significant effects on capacity than variables such as entry angle and entry radius. These findings could thus contribute to an improved understanding of the variables that affect entry lane capacity and therefore the development of better roundabout capacity models.

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[87-A] Roundabout Capacity (ASCE).pdf - Accepted Manuscript
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More information

Accepted/In Press date: 22 January 2015
Published date: 10 March 2015
Organisations: Transportation Group

Identifiers

Local EPrints ID: 381546
URI: http://eprints.soton.ac.uk/id/eprint/381546
ISSN: 0733-947X
PURE UUID: f103416d-20a1-49e6-b4a8-cf4ddca52df9
ORCID for Ben Waterson: ORCID iD orcid.org/0000-0001-9817-7119

Catalogue record

Date deposited: 16 Sep 2015 12:51
Last modified: 15 Oct 2019 00:50

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